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FEATURE // BY JODI ASBELL-CLARKE, ERIN BARDAR, ELIZABETH ROWE, TEON EDWARDS,
JAMIE LARSEN, BARBARA MCEACHERN, AND KATIE STOKINGER
Digital Games
for Implicit Science Learning
In the free-choice game Impulse, players try to get their
green ball to the goal without crashing into the other balls as
they build a tacit understanding of Newton’s laws of motion.
T
he tablet screen displays a swirling blue circle in the
upper left corner. A green ball is to the right. An arrow
next to the ball and pointing in the direction of the swirling blue goal calls out for a tap to the screen. You tap near the
green ball and it slowly moves toward the goal and enters it.
The goal disappears to reappear in a new location along with
some red balls now floating around the space. Another tap
moves the green ball toward the new goal but this time some
of the red balls are in the way. How do you avoid them?
What happens if they collide with the green ball? Can you
tap the screen to move the red balls too?
Creating Fun Games with a Purpose
The swirling blue goal and single green ball are the simple
start of Impulse, a digital game developed by the Educational
Gaming Environments (EdGE) group at TERC. It is one of
several games being designed and tested by EdGE as part of
a research effort to investigate implicit science learning in
game-based learning environments.
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TERC HANDS ON! FALL 2015
In EdGE we view games, like most forms of play, as a way to
build implicit knowledge—knowledge that is not yet formalized in learners’ minds (Polanyi, 1966). We seek to design
games that kids do not view as educational. Instead we aim to
create free-choice games—public games that people choose
to play in their own time.
Players build foundational tacit knowledge from repeated,
and increasingly complex, experiences in a game. They
grapple with the game mechanics—the rules and challenges
of the game—and in doing so they learn. In some games
this learning can take place in meaningless or perhaps even
socially unproductive contexts, but the EdGE games are
designed to allow players to dwell in science. Players generalize solutions that help them become intuitively familiar
with scientific phenomena that ground each game through
the ongoing gameplay.
Impulse is built around Newton’s laws of motion. It immerses
players in a particle simulator where they must predict
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In Quantum Spectre, a puzzle-style
EdGE game, players use flat and curved
mirrors, lenses, and other optical
instruments to get lasers to hit targets.
“
EdGE games are designed to allow players
to dwell in science.
”
Newtonian motion in order to successfully avoid collisions
and reach the goal. The particles—balls of different colors—
obey Newton’s laws of motion and gravitation. Players use
an impulse, triggered by their touch or click, to apply a force
to the balls. If the green ball collides with any ambient ball
(red balls in the earlier example), the level is over and the
player must start again. Each level of the game gets more
complex, requir-ing players to contend with the gravitational
forces of an increasing number of balls and also balls of
different mass (and thus inertia). Within each level, players
may impart up to 20 impulses. Each impulse depletes the
energy available (measured by a green bar in the right
corner). Once the 20-impulse quota is reached, the player no
longer has energy left to apply additional forces to the balls.
Studying Game Play
Digital games generate a stream of player-activity data,
which can be captured through digital logs. This data exhaust
(Owen, Halverson, and Willis, 2012) can be used along with
educational data mining (EDM) methods to detect learners’
patterns of play and reveal how those patterns change as players advance toward more successful and sophisticated gameplay (Baker and Yacef, 2009; Martin., et al, 2013). EdGE has
built data mining detectors to “watch” implicit learning in
our games. By analyzing the data logs generated during digital
gameplay, we can detect the patterns in gameplay that are
consistent with an understanding of the scientific phenomena underlying the game design.
In order to identify starting points for
what to look for in the data logs, we
reviewed video of more than 70 high school
students playing Impulse. We began to identify strategic moves that seemed related to the
physics of the game (Asbell-Clarke, Rowe, and
Sylvan, 2013). Players were observed to develop
gameplay tactics such as “let it float”—letting a ball
stay in constant motion without exerting an external
force (Newton’s first law of motion). Players also
talked about wanting to stay away from the “heavy
ones” because they take so many clicks to move, a strategy consistent with an implicit understanding that you would
need to apply more force to redirect the heavier balls than you
would to change the motion of the lighter ones (Newton’s
second law of motion).
Through data mining, we have detected patterns of gameplay
in Impulse that appear to show evidence of the same strategic
moves identified in the video observations. The “let it float”
strategy seen in the videos was also evident in the data logs.
This strategy demonstrates an intuitive understanding that
the ball will remain moving at the same speed and in the same
direction if no external force is applied. While seemingly
simple, this concept is elusive for many learners (McCloskey,
1983; diSessa, 1993), likely because we don’t live in a frictionless, gravity-free world. There are nearly always external
forces upon us but not in the ideal world of a digital game. In
the logs, we also saw evidence that players use more force to
push the heavier balls than the lighter ones, which is consistent with an intuitive understanding of Newton’s Second
Law: Force = mass x acceleration.
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FEATURE // CONTINUED
Digital Games
for Implicit Science Learning
With the return of Zoombinis,
an award-winning game
by TERC from the ‘90s, EdGE
is researching players’
computational thinking skills.
In the higher levels of the game, there are gray balls that have
a heavier mass but a smaller diameter than the other balls.
This was to differentiate if players were reacting to size or
mass when deciding to use more force. Indeed, they used
more force for the gray balls than any of the others, indicating
that they were correctly reacting to the mass (Rowe, AsbellClarke, and Baker, 2015). Although the game does not explicitly explain, or even mention, Newton’s laws, players are
demonstrating through their gameplay that they understand
the physics—at least at an implicit level.
Newton’s laws, the students show greater learning gains on
related test questions compared to students who didn’t play
the game or didn’t have the teacher-led game-to-curriculum
scaffolding. This is particularly true for students in nonhonors and non-AP science classes, suggesting that games
may be a powerful vehicle for supporting students who have
been placed in lower level tracts for science learning (Rowe,
Asbell-Clarke, Bardou, Kasman, and MacEachern, 2014;
Rowe, Bardar, Asbell-Clarke, Shane-Simpson, and Roberts,
in press).
Bridging Game-Based Learning to the Classroom
Next Steps for EdGE
One long-term goal of our work is to use the data we collect
from the gameplay to create a personalized, adaptive gaming
experience for learners and to help teachers use the data to
inform classroom instruction and discussion. We hypothesize that if teachers use examples from games, drawing on
implicit game-based learning to “bridge” to explicit curriculum outcomes, students will be better prepared to learn new
concepts in the classroom. Our early research suggests that
when high school students play Impulse and their teacher
uses and discusses examples from the game when teaching
We are further exploring and building upon our model of
game-based implicit learning through several research and
design initiatives. This includes studying new constructs,
such as computational thinking, the use of using digital
games to get people outdoors, the enhancement of available
tools for bridging games and schools, and the includion of
physiological, psychological, social, and neurological data
sources in our research to build a more complete picture of
implicit game-based learning. (See About EdGE page 17.)
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In the SportsLab gaming environment, students develop 21st Century
skills while competing in a parkour shoe design competition.
ABOUT EdGE
The Educational Gaming Environments (EdGE) group
at TERC is a team of designers, educators, and
researchers working together to study how game-based
learning can be measured and then used for teaching
and learning in and out of classrooms. Over the past
six years, EdGE has been building games in online
and wireless environments for the public so that they
can grapple with intriguing mystery, puzzle, and
action games grounded in science. Players learn how
to survive in the wild as a bird, use mirrors to direct
lasers through complex puzzles, or apply Newtonian
mechanics to guide their ball to a goal without
collisions. Players persist because they are having
fun, and EdGE research—which involves looking at
the “click” data generated through digital gameplay—
shows that players are learning at the same time.
Selected EdGE Initiatives: Zoombinis and
Computational Thinking—The Logical Journey of the
Zoombinis was the first in a series of three computational
thinking games developed by TERC in the 1990s. TERC and
partners are re-launching Zoombinis for wireless devices
(e.g., tablets) and new operating systems to reach a large
commercial audience ranging from ages eight through
adult. Building on prior research, EdGE is studying the
cognitive strategies that emerge through Zoombinis game
play. Researchers are looking at the data logs and
employing other digital methods to study collaboration and
social interaction in middle school classes that support
the learning of computational thinking—the set of skills
and understandings that learners need as they learn to
program and build algorithms in computer science.
STEMLandia and Getting Folks Outdoors—When
EdGE was founded in 2009, the aim was not to make
more gamers, but rather to make all the time kids spend
in games more productive. This evolved
into a mission to also use digital games as
a vehicle to get kids back outside. Through
the STEMLandia project (STEMLandia.com),
EdGE is using location-based games,
like Geocaching, to build STEM puzzles
discoverable by exploring the local
environment. EdGE is also looking at ways
to add augmented reality tools to these outdoor games
to allow learners to see the past, present, future,
and imaginary changes of the world around them.
Taking Games to School and Bridging Games and
Curricula—EdGE is building tools to help teachers use
their students’ game-based implicit learning to help
teach explicit science learning in the classroom. By
providing teachers access to the same types of data
that EdGE researchers use to study learning—and doing
so in ways geared toward the needs of those teachers
and the realities of classrooms—teachers will be better
prepared and informed about what to do next in their
teaching. Knowing where their students are in a game,
what strategies they are developing, and where they are
getting stuck, teachers can customize their lessons
to get at the material kids need to work on.
Revealing the Invisible and Additional Measures—
With MIT and Landmark College, an institute for higher
learning for students with dyslexia, ASD, and ADHD,
EdGE is examining how to infuse eye-tracking and other
sensor data into game-based learning logs to inform the
development of adaptive games that provide customized
experiences to accommodate different learning styles.
SportsLab—EdGE is developing and testing
SportsLab, a collaborative game-based interactive
environment where students, ages 12-18, participate
in a sport-product design challenge, such as designing
a parkour shoe. Each team creates and submits a
REFERENCES
Asbell-Clarke, J., Rowe, E., & Sylvan, E. (2013, April). Assessment design for
emergent game-based learning. Work-in-progress presented at the ACM SIGCHI
Conference on Human Factors in Computing Systems (CHaI’13). Paris, France.
Baker, R.S.J.d., & Yacef, K. (2009). The state for educational data mining in
2009: A review and future visions. Journal of Educational Data Mining 1(1), 3-17
diSessa, Andrea A. (1993). Toward an epistemology of physics. Cognition and
Instruction, 10(2/3), 105-225. doi: 10.2307/3233725
Owen, E., Halverson, R., & Willis, N., (2012). CyberSTEM: Gamebased learning telemetry model for assessment. Presentation at 8tth
Annual Games+Learning+Society, Madison, WI.
Martin, T., Aghababyan, A., Smith C., Olsen, D., Pfaffman, J., Phillips, R., Baker, S.,
& Janisiewicz. P., (2013). Nanogenetic learning analytics: Illuminating student
learn-ing pathways in an online fraction game. Paper presented at the Proceedings
of the Third Conference on Learning Analytics and Knowledge. Leuven, Belgium.
McCloskey, M. (1983). Intuitive physics. Scientific American, 248(4), 122-130.
Polanyi, M. (1966). The tacit dimension. Chicago, IL: University of Chicago Press.
concept model and pitch for a product
design. Participants, sport researchers,
and product experts determine the best
pitches with awards for top designs.
SportsLab brings pedagogical frameworks
from game- and project-based learning
together with a design challenge that
fosters learning and understanding of 21st
Century skills and STEM concepts. The ultimate goal
is to test the effectiveness of a game-based STEM
and ICT-infused design challenge in collaboration with
industry partners as a way to motivate disengaged
youth in ways that lead to potential STEM career paths.
The EdGE team is led by Jodi Asbell-Clarke and
co-founders, Teon Edwards and Jamie Larsen. Elizabeth
Rowe is the director of research, Erin Bardar is in charge
of educational materials, Barbara MacEachern leads
outreach and communication, and Katie Stokinger
manages day-to-day operations. EdGE collaborates
with research partners such as Columbia University’s
Teachers’ College, North Carolina State University,
and New Knowledge Organization.
EdGE Research is conducted through several initiatives including
projects funded by the National Science Foundation under grants
DRL-1119144, DRL-1415284, DRL-1502882, and DRL-1417967.
Any opinions, findings, and conclusions or recommendations
expressed in this material are those of the author and do not
necessarily reflect the views of the National Science Foundation.
Building bridges: Teachers leveraging game-based implicit science learning in
physics classrooms. To appear in D. Russell & J. Laffey (Eds). Handbook of Research
on Gaming Trends in P-12 Education. Hershey, PA: IGI-Global.
Rowe, E., Asbell-Clarke, J. & Baker, R. (2015). Serious game analytics to measure
implicit science learning. In C.S. Loh, Y. Sheng, & D. Ifenthaler (Eds.), Serious
Game Analytics: Methodologies for Performance Measurement, Assessment, and
Improvement. New York, NY: Springer Science+Business.
Rowe, E., Asbell-Clarke, J., Bardar, E., Kasman, E., & MacEachern, B.
(2014). Crossing the bridge: Connecting game-based implicit science
learning to the classroom. Paper presented at the 10th annual Games
+Learning+Society conference in Madison, WI.
TO LEARN MORE:
@EdGE_at_TERC
edge.terc.edu
facebook.com/EdGEatTERC
Rowe, E., Bardar, E., Asbell-Clarke, J., Shane-Simpson, C., & Roberts, S. (in press).
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